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GPT-4o-mini Search Preview vs Ministral 3 3b Instruct 2512
This page is context-first: how much text each model can take in one request. Full specs adds capabilities and limits; the pricing matrix below is only about $/million tokens from hosts that list both models.
Model
GPT-4o-mini Search Preview
Context window
128K
128,000 tokens · ~96K words
Context window · side by side
Bar length is relative to the larger of the two windows (100% = max of this pair). This is not pricing.
Ministral 3 3b Instruct 2512 has about 2× the context window of the other in this pair.
Ministral 3 3b Instruct 2512 has 100% more context capacity (256K vs 128K tokens). Ministral 3 3b Instruct 2512 is 33% cheaper on input.
Quick verdicts
Short takeaways — validate with your own workloads.
Long document processing
Use Ministral 3 3b Instruct 2512. Its 256K context fits entire documents without chunking (vs 128K).
RAG / high-volume retrieval
Use Ministral 3 3b Instruct 2512. Input tokens are 33% cheaper — critical when sending large retrieved contexts.
Long output (reports, code files)
Use Ministral 3 3b Instruct 2512. Its 256K max output lets you generate complete artifacts in one request.
Full specs
Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.
| Spec | GPT-4o-mini Search Preview | Ministral 3 3b Instruct 2512 |
|---|---|---|
| Context window | 128,000 tokens (128K) | 256,000 tokens (256K) |
| Max output tokens | 16,384 tokens (16K) | 256,000 tokens (256K) |
| Speed tier | Fast | Fast |
| Vision | Yes | No |
| Function calling | Yes | No |
| Extended thinking | No | No |
| Prompt caching | Yes | No |
| Batch API | Yes | No |
| Release date | Mar 2025 | N/A |
Pricing matrix
Dollar rates only: hosts that list both models, per 1M tokens. For how much text fits, use the context section above — not this table.
| Provider | GPT-4o-mini Search Preview in | GPT-4o-mini Search Preview out | Ministral 3 3b Instruct 2512 in | Ministral 3 3b Instruct 2512 out |
|---|---|---|---|---|
| Fireworks | — | — | $0.100/M | $0.100/M |
| Openai | $0.150/M | $0.600/M | — | — |
Frequently asked questions
Powered by Mem0
Use a smaller model.
Get better results.
Mem0 gives your AI long-term memory so you stop re-sending context on every call. That means you can use a smaller, faster, cheaper model — and still get better answers.
Example: a multi-turn chat session
80% less to send — works with any model